Tracking mcmapply with progress bar
pbmcmapply is a wrapper around the mcmapply function. It adds a progress bar to mcmapply function.
Parallelization (mc.core > 1) works only on *nix (Linux, Unix such as macOS) system due to the lack of fork() functionality, which is essential for mcapply, on Windows.
pbmcmapply(FUN, ..., MoreArgs = NULL,
mc.style = "ETA", mc.substyle = NA,
mc.cores = getOption("mc.cores", 2L),
ignore.interactive = getOption("ignore.interactive", F),
mc.preschedule = TRUE, mc.set.seed = TRUE,
mc.cleanup = TRUE)FUN |
the function to be applied in parallel to ... |
... |
arguments to vectorize over (vectors or lists of strictly positive length, or all of zero length). |
MoreArgs |
a list of other arguments to FUN. |
mc.cores |
see |
mc.style, mc.substyle |
style of the progress bar. See |
ignore.interactive |
whether the |
mc.preschedule, mc.set.seed, mc.cleanup |
See |
# A lazy sqrt function which doesn't care about efficiency
lazySqrt <- function(num) {
# Sleep randomly between 0 to 0.5 second
Sys.sleep(runif(1, 0, 0.5))
return(sqrt(num))
}
# On Windows, set cores to be 1
if (.Platform$OS.type == "windows") {
cores = 1
} else {
cores = 2
}
# A lazy and chatty sqrt function.
# An example of passing arguments to pbmcmapply.
lazyChattySqrt <- function(num, name) {
# Sleep randomly between 0 to 0.5 second
Sys.sleep(runif(1, 0, 0.5))
return(sprintf("Hello %s, the sqrt of %f is %f.", toString(name), num, sqrt(num)))
}
# Get the sqrt of 1-3 in parallel
result <- pbmcmapply(lazySqrt, 1:3, mc.cores = cores)
chattyResult <- pbmcmapply(lazyChattySqrt, 1:3, MoreArgs = list("Bob"), mc.cores = cores)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.